Mark,
if I understand what you are asking, then you likely want either the
Floyd-Warshall algorithm:
http://en.wikipedia.org/wiki/Floyd-Warshall_algorithm
or Djikstra's algorithm
http://en.wikipedia.org/wiki/Dijkstra%27s_algorithm
The package igraph seems to have some useful methods, (The
shortest.paths method is probably what you want, I think).
How large a graph are we talking about here?
Haris Skiadas
Department of Mathematics and Computer Science
Hanover College
On Mar 4, 2008, at 9:03 PM, Mark W Kimpel wrote:
> I am doing some work the Rgraphviz, a Bioconductor package, but
> since my
> question is of a more general nature, thought I would send to this
> list
> in hopes that a graph theory expert could answer my question.
>
> I wish to do some statistics on node-node relationships. In
> particular,
> I want to see if two connected nodes share a common property. I
> believe
> that the more "connected" the two nodes are the more likely it
> would be
> that they share the property. The graph is highly connected, with a
> large majority of nodes connected in some fashion.
>
> My first question is: can anyone make this real easy and tell me if
> this
> has been done and how?
>
> If not, I need to start with developing a measure of connectedness
> that
> includes degrees of separation and number of edges at each degree. The
> highest level of connectivity, with weighting 1, would be a first
> order
> connection (the graph is undirected). Beyond that, of course, it gets
> more complicated. To begin, I need to identify the best path
> between two
> nodes then characterize that path.
>
> Rgraphviz seems to have a fair amount of rendering capabilities, but I
> don't see many functions to statistically analyze the graph.
>
> Thanks,
> Mark
> --
>
> Mark W. Kimpel MD ** Neuroinformatics ** Dept. of Psychiatry
> Indiana University School of Medicine
>
> 15032 Hunter Court, Westfield, IN 46074
>
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>